Sex-related differences in the applicability and performance of the Montreal Cognitive Assessment in the acute phase of stroke
Bibliographic record
Abstract
INTRODUCTION: Early cognitive screening, although recommended, can be challenging in acute stroke settings. In patients with acute stroke, we aimed to evaluate (1) reasons and predictors of non-applicability of the Montreal Cognitive Assessment (MoCA) and (2) MoCA score performance, focusing on sex-related differences. PATIENTS AND METHODS: We conducted a single-centre study on patients consecutively admitted to our stroke unit (June 2019-June 2023). Reasons for MoCA non-applicability and MoCA scores were compared between sexes. Univariate and multivariable analyses explored associations between MoCA applicability and sociodemographic/clinical characteristics. RESULTS: Out of 637 admitted patients (median age 78.8 years; 54.3% male; 81.2% ischemic stroke), 445 (69.8%) completed the MoCA (76.3% of males, 62.2% of females, P <.001). Reasons for non-applicability were acute stroke-related in 63.5% of cases (mainly altered consciousness and aphasia), prestroke conditions-related in 22.9% and other (refusal/unreported) in 13.5%. Stroke-related reasons were more frequent in females (P =.002) and refusal in males (P =.005). Variables associated with MoCA non-applicability were: NIHSS on admission in both females (adjusted odds ratio [adj.OR] 1.25, 95% CI, 1.16-1.34) and males (adj.OR 1.24, 95% CI, 1.14-1.34); pre-stroke mRS in females (adj.OR 1.58, 95% CI, 1.15-2.17) and years of education and left-hemisphere lesion in males (adj.OR 0.91, 95% CI, 0.84-1.00 and adj.OR 2.38, 95% CI, 1.16-4.86, respectively). Among tested patients, females showed lower raw and adjusted MoCA scores (P <.001 and P =.022, respectively). CONCLUSION: Sex-specific factors influence feasibility and interpretation of early cognitive screening in the acute stroke phase: recognising these differences might guide future efforts towards more inclusive and individualised protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".